A recent study led by Anil Menon of the University of California, Merced and Baobao Zhang of Syracuse University finds that Americans’ concerns about losing jobs to artificial intelligence remain largely unchanged, even when they are told such changes could happen soon.
The research surveyed 2,440 adults in the United States to gauge how people respond to predictions about the arrival of “transformative AI,” with projected timelines ranging from as early as 2026 to as late as 2060. Participants were randomly assigned to read scenarios indicating different years for when job-disrupting AI might emerge or received no timeline at all.
The study found that shorter timelines made respondents only slightly more anxious about automation’s impact on employment. However, these warnings did not significantly change their beliefs about when job losses would occur or their support for government policies like retraining programs or universal basic income.
“These results suggest that Americans’ beliefs about automation risks are stubborn,” said the authors. “Even when told that human-level AI could arrive within just a few years, people don’t dramatically revise their expectations or demand new policies.”
According to Menon and Zhang, the findings challenge assumptions that making technological threats seem more immediate will lead to greater public support for regulation or social safety nets. The survey showed only modest increases in concern after reading any timeline scenario, with the group told AI would arrive by 2060 reporting a slight increase in worry—possibly because this forecast seemed more credible than predictions of imminent disruption.
The study draws on construal level theory, which looks at how perceptions of time influence risk judgments. Despite growing awareness of automation risks across all groups exposed to timelines, participants’ economic outlooks and policy preferences remained stable.
Menon and Zhang noted several limitations: their research focused on how timeline cues affect attitudes but did not explore other psychological factors such as trust in expert forecasts or beliefs about economic trade-offs. They also acknowledged that the survey cannot measure shifts in individual opinions over time.
“The public’s expectations about automation appear remarkably stable,” they said. “Understanding why they are so resistant to change is crucial for anticipating how societies will navigate the labor disruptions of the AI era.”
